The objective of this thesis is to implement and evaluate dynamic resource allocation
algorithms that adjust the fairness of an OFDMA network. We consider the category
of Rate Adaptive algorithms where the Base Station is assumed to transmit at full
power and under this condition we try either to maximize the throughput of the
system or to maximize the minimum rate of the users. The novelty within the
implemented algorithms lies in the adaptive adjustment of the system fairness, an
index that shows how fair the throughput of the system is split to the users. The
adjustment is performed in general by reallocations of channels and power. Two
approaches of adjusting the system fairness were implemented: The Fairness based
Sum Rate Maximization with Proportionalities (FSRM-P) and the Fairness Based
Max-Min Rate (FMMR). For each approach we initially formulate the optimization
problem and then we evaluate three solutions. Because of the non-convex nature of
the problems, the proposed novel solutions are iterative, heuristic and in general suboptimal.
The evaluation is performed by considering the downlink of a single
OFDMA cell serving a set of users which have different rate requirements. The
algorithms whether an increase or decrease of the fairness is required, are able to meet
the target. However this always comes at the cost of an opposite effect on throughput.
Simulations results showed that for the same value of system fairness, the FSRM-P
performs better in terms of throughput while the FMMR is able to be fairer with the
users. Moreover, in most cases the FMMR achieves higher user satisfaction, however
when the rate requirements of the users are increased the satisfaction drops to lower
levels than the FSRM-P.